The North Carolina unemployment insurance experiment may be looking up

The benefits have been stopped, and there has been much recent debate over how well this is working to stimulate reemployment. This new study is from Kurt Mitman, who is a doctoral candidate at U. Penn and an NBER research associate, here is his summary:

1. Evidence from the establishment survey conﬁrms a substantial increase in employment in North Carolina following the unemployment insurance reform.

2. The increase in payroll employment reported by the sample of North Carolina employers is smaller than the increase in employment reported by workers in the household survey.

3. The increase in employment [is] driven by the private service sector.

4. A comparison of the growth in employment between North Carolina and the adjacent states in Figure 5 reveals a similar growth in the post-reform period between the two Carolinas, which is much faster growth than in Virginia.

Perfectly reasonable. I just thought you would have more thoughts on the brief as a whole!

This post won’t add to a discussion unless you add thoughts to it. But I see you did the same type of post for previous studies on the (North Carolina) subject. Regardless I look forward to your comprehensive post on unemployment insurance.

I will admit that I am slightly confused why there would be “limited data” here. The CPS should have enough information where even a simple diff-in-diff design might prove that the trend is statistically insignificant (which is probably the case). But again that is not the point of this post.

The Economic Issue seems pretty straightforward to me, but, unless I’m missing something, Some People who do not Secure Employment will have Their Standard of Living Decline. Political Economy should, at the very least, have Some Data on this aspect of the issue. However, between this issue, the Minimum Wage, the Minimum Wage for Teens, the Minimum Wage Worldwide, Etc., I’m beginning to Need a Scorecard.

For an economist to call it an “experiment” illustrates the biggest problem with economics today.

Where is the experiment design laid out?
What are the experiment controls?
How are the results measured?
Who and how is the experiment results collected?

Natural scientists get skewered by economists for presenting results from research that collect huge amounts of new data and then presenting likely cause and effect. And when alternate explanations are offered, scientists go out and spend a lot of effort collecting new data to include or exclude those alternative explanations. And those reports get skewered because they present results economists don’t like, so scientists go collect more new data in different ways from different sources resulting in the same conclusions with the same attacks from economists who don’t like the results.

The evidence for climate change caused by human activity has yet to be disproved by hundreds of studies designed to disprove it. Ie, the reason for warming is the sun is getting hotter was an alternate explanation, so scientists put satellites in space to measure the sun with no trend of increased output as the global temperature warms. And so on for all the other criticism.

Economists never seem willing to put any effort into collecting new data. Never deviate from their list of causes even when their causes hardly seem to be factors in what they call “experiments”.

Its always government that is the cause of bad things, and the “market” for every positive effect.

Taxes are too high, even though tax revenues have been at six decade lows for the past five years.

Regulation is too tight even with industry causing disaster after disaster from toxic chemical leaks to towns being destroyed in industry accidents to large environmental harms. And some want to adopt China policies that has resulted in smog worse than the LA smogs that spurred the Clean Air Act and the auto an truck pollution controls, and worse than the killer London fogs that marked the real arrival of the industrial age.

The “result” of the “experiment” will be widely debated with lots of selective use of existing data which offers no explanation used to “prove” unambiguously that unemployment benefits cause unemployment, I’m sure.

That how economists create “experiments”: to passively prove dogma.

After all, work is bad for an economy, it is a deadweight loss to profits for any work to be done in an economy, so economists will never work to collect new data.

No one said “controlled experiment”. The reality is that incidental experiments are all we will ever get when it comes to macro-economics because no one is going to let me take an entire state, and randomly assign unemployment benefits to some and not others, just to see what would happen. In fact it’s not much different from climate science because they also are not allowed to run controlled experiments (hey we’re going to ramp CO2 output way up to test our theory!).

Regardless, economists often make the same mistakes as climate change scientists. They build big fancy models to explain the world and forecast the future but the models are shown to not be robust again and again and again, but the models supporters continually assert that the models are good despite their inability to predict real world outcomes.

Does the failure of their model mean global warming isn’t caused by humans? Not at all, but we should take their extreme disaster do-something-now scenarios with as much skepticism as when the President’s economic team tells us we need to pass the stimulus because their model shows unemployment disaster if we don’t do it.

Your argument about regulation is a straw man — most economists believe that environmental regulations are necessary because you have a market failure when polluting water or air.

“The evidence for climate change caused by human activity has yet to be disproved by hundreds of studies designed to disprove it.”

Really, there is absolutely no doubt at all? And serious climate researchers are 100% certain in their findings?

“Taxes are too high, even though tax revenues have been at six decade lows for the past five years.”

The first part of this sentence presumably talks about tax rates (as that is what is being complained about) whereas the second part talks about absolute levels. Therefore, leaving aside the accuracy of the assertion that tax revenues are at six decade lows, they do not necessarily have anything to do with each other? Ever heard of the laffer curve?

“Regulation is too tight even with industry causing disaster after disaster from toxic chemical leaks to towns being destroyed in industry accidents to large environmental harms.”

You are a) jumping to the conclusion that regulation is the answer, b) that all regulation is good because some of it is and c) that there are no trade-offs to regulation. And your point about China and early-industrial age Chinese smog only proves that it is economic progress that leads to reduction in emissions.

If tax rates were 100%, and zero tax revenue was collected, would the lack of tax revenue mean that tax rates were clearly not high enough? The fact is that we have the highest rates of the developed world. FACT, not dogma. Ignore for a second that many large multi-national companies don’t pay that full rate — that is because a company with HQ in the US has subsidiaries in other countries, and they keep their earnings in those countries to avoid having to pay the higher rate (if they repatriate the cash, it is subject to the US tax rate minus foreign taxes paid). Note that this is harsher than what most countries do — a territorial based tax system that allows for taxes to be paid in the countries where the revenue was earned. The US is one of 6 countries to do worldwide-based taxation, except that our rate is higher than the other 5.

On the other hand, every US-based company that only operates in the United States, pays the full rate (minus any special tax credits they might have such as faster depreciation of assets on corporate jets or oil refining equipment, “green” tax credits, etc., distortionary effects that most good economist are against).

We are at a disadvantage to corporations in every other country because of this high, uncompetitive rate. And to deny that, is denying that the supply curve is upward sloping and the demand curve is downward sloping.

If your model is going to explain the increase in employment from June to November it should explain the decrease that proceeded it. Virginia, North Carolina, and South Carolina are quite different to begin with. Virginia has a large federal government and contractor employment. North Carolina has the tech triangle and the Charlotte financial hub.

Unless this “experiment” produces a miricale or disaster, one should expect the results to be inclusive when viewed through the lense of total employment statistics.

What really strikes me from this study is how similar North and South Carolina are, despite the benefit cuts up north. We can state with confidence that a lot of people in NC lost income from the “experiment”. Any other conclusions seem premature.

I suppose it could be the case that there is always a lot of noise in these series, and we’re all so keyed into trying to find a signal in the North Carolina data that we’re finding narratives in the randomness. Because, for instance, it looks to me like in North Carolina, and now in the last few months nationally, there have been unusual declines in labor force participation leading up to the end of EUI. But these declines don’t seem to have any relationship to a decline in EUI recipients.

It has me wondering if there is a sort of priming effect going on. This is survey data, after all, and we take movements of just a few tenths of a percent to be big news. There must be millions of workers in their 50’s and 60’s who are within a decade of retirement. There are no hard and fast targets for these people. They’ve saved some, the kids have moved out and their expenses are going down, they will have social security and medicare coming. So they are in this grey area where they might like some more earnings before they retire, but it’s a sliding scale, which depends in part on their available opportunities. I happen to have a similar problem. If I were contacted by the CPS surveyors, I would not know what category to tell them I’m in.

So, there are a million or so long-term unemployed workers who have the dilemma we general talk about on this topic, and a change in EUI policy will have an effect on their circumstances and their labor decisions.

But, there are millions of others who are simply hard to categorize, and whose choice of a category may be subtly primed by the state of the economy, the stance of public policy, etc.

The problem is, we can’t distinguish the two groups in the survey data. So, there might be a big pile of cases that move from unemployment to employment or not in labor force because their situations change. But, there might be a million who move to not in labor force who really have had no change at all. The scale of the shift since June, and especially since earlier in the year leading up to June, in North Carolina, for instance, dwarf the actual number of EUI beneficiaries. Nationally, less than 1% of the labor force is still on EUI. Labor force participation is down by about 1% in NC since June and 2% since the start of 2013. It’s an aberration, but it couldn’t be explained by just looking at EUI beneficiaries.

Good points, but I would add another one I don’t think has been mentioned.

There are multiple ways to leave the state labor force, and one is to move to another state. NC residents saw an influx of new people moving to NC for jobs in years when the unemployment rate was lower than the US average (late 90’s) or even just when it was lower than the state of their previous residence. I have not yet seen any statistics that would quantify whether the reverse is happening now but I would suspect that a portion of the labor force loss is people leaving for elsewhere, whether that’s back to their previous state of residence or on to some more promising future one.

“It is very important to recognize before proceeding any further, that one cannot derive definitive conclusions about the effects of unemployment benefit programs on the labor market from the analysis of the experience of a single state. Decisions of even a single large employer, which may be unrelated to to the unemployment insurance reform, may have an impact on the statistics. It is also hard to isolate the impact of the reform from the impact of weather, other policy changes, changes in interstate migration decisions, changes in the determinants of the decisions to enter the labor force or retire, etc. Moreover, only a few months of data are available and sample sizes available in most data sets are too small to yield reliable predictions of month to month changes in variables such as employment, unemployment, etc. So the evidence provided below should be interpreted with extreme caution.”

The plural of anecdote is not data, in other words.

Simple visual inspection (say) of the North versus South Carolina rate makes it hard to suggest the NC reform was responsible for miracles. Unemployment rates dropped in both states over late 2013. It starts dropping slightly sooner in NC, but that’s all. The authors are going to have to start doing some actual econometrics.

“Simple visual inspection (say) of the North versus South Carolina rate makes it hard to suggest the NC reform was responsible for miracles. Unemployment rates dropped in both states over late 2013. It starts dropping slightly sooner in NC, but that’s all. The authors are going to have to start doing some actual econometrics.”

I thought the point was that there was an expectation that since North Carolina stopped unemployment benefits early there would be a negative effect due to the loss of Federal income and a drop in consumption spending, instead there’s no evidence that North Carolina did any worse than South Carolina, even though South Caroline was still spending hundreds of millions of dollars on unemployment benefits.

There were claims in BOTH directions. A lot of conservatives claimed that extended unemployment benefits would lessen people’s preference to work. Is that presumed now to be disproven, by SOUTH Carolina? What if unemployment benefits don’t have any effects at all, on future employment-population ratios? Shouldn’t we then extend unemployment insurance to help people until the economy really gets booming?

Comparing VA to SC and NC here, like the authors do, is an excellent example of how to lie with statistics. Virginia’s unemployment rate, at about 5.6% or so, is a good 2.4% below North Carolina’s and has been for years. Virginia is far closer to full employment than either of the Carolinas. One can ascertain this fact by looking at the y-axis labels, on the charts in the paper, however, the axes are not directly eye-comparable as the range shifts between the Carolinas (centered on 8-10%) and VA (centered on 5-7%). It seems very hard to believe that the unemployment and labor force participation rate dynamics are the same when one is very close to full employment (like VA) versus when one is stuck in years of high unemployment (like the Carolinas). With Virginia removed, we see no difference between the economic performance of the Carolinas, making the answer to the UI question look dramatically different.